Low-Rank Hankel Signal Model: Numerical Results

Lucas Abdalah, Walter da Cruz Freitas Jr., Pedro Marinho Ramos de Oliveira, Vicente Zarzoso

DOI: 10.14209/sbrt.2021.1570727304

Evento: XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2021)

Keywords: Vandermonde Decomposition Hankel Matrix Singular Value Decomposition

Abstract

Hankel matrices arise in several applications of signal processing, such as tensor decompositions, biomedical signal processing, etc. In general, these techniques rely on digital signals that can be modeled as a linear combination of exponential polynomials. Hence, the Hankel matrix built from these signals presents full rank, equal to the number of poles, ensured under mild constraints. The present work observes other features of the low-rank Hankel model, using singular value decomposition (SVD) to assess rank deficiency. The effects observed may impact blind source separation (BSS) problems.

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